Virtual shape generation method and device using the same

ABSTRACT

The present invention is to propose a method and device which evaluate the shape and the size of each part of a human body in a multidimensional manner, generate a distribution map thereof, and compute and realize a virtual shape located in the periphery of the distribution map, whereby the shape and the size of a product such as clothing can be modified and designed. The virtual shape forming unit computes a space distortion function which mutually distorts three-dimensional shape data of a plurality of people, generates a multidimensional distribution map thereof based on the size of the distorted space, and derives a virtual shape which exists on an arbitrary location of the multidimensional distribution map.

TECHNICAL FIELD OF THE INVENTION

[0001] The present invention relates to a virtual shape generationmethod and a device using the same for modifying and designing the shapeand the size of a product so as to correspond to those of a human body.

DESCRIPTION OF THE RELATED ART

[0002] When a product, such as clothing adjusted to a customer, isdesigned as not a custom-made product but a mass production product fora group (a specific customer bracket), a group having a similar shape isextracted from among a distribution map of a plurality ofthree-dimensional human body shapes to design the product that isadjusted to the group. In this case, not only product design for theaverage shape representing the group, but also compatibility evaluationof the product to a virtual shape located in the periphery of thevariations of the group must be needed.

[0003] To achieve this, there are required:

[0004] (1) creation of the distribution map of a plurality ofthree-dimensional human body shapes that are described using numericaldata;

[0005] (2) creation of a virtual shape located in the periphery of thedistribution map; and

[0006] (3) a consistent method and a device using the same for realizingthis virtual shape.

[0007] Particularly, since the distribution of the three-dimensionalhuman body shapes cannot be sufficiently represented by means of alinear distribution such as one distributed in a “smaller to larger”manner, multidimensional distribution map in which the shape and thesize of the human body are represented must be derived. For example, ina linear distribution such as one distributed in the “smaller to larger”manner, a person having “the shortest height, the shortest waist girth,the shortest legs, and the smallest head among the group” at the sametime and a person having “the tallest height, the largest waist girth,the longest legs, and the largest head among the group” at the same timestand on the opposite extremes of the group. However, those having suchcharacteristics hardly exist. Accordingly, there have been expected theconsistent generation method and generation device for computing andrealizing the virtual shape located in the periphery of the distributionobtained after evaluating the shape and the size of each part of thehuman body in a multidimensional manner.

[0008] As a method for obtaining the distribution map ofthree-dimensional human body shapes, an art is known in which, byre-describing the human body shape using a B-spline function, thedistribution is obtained using the parameter of the function (TaizouKishimoto, Susumu Kureno, Takao Kurokawa, and Akihiro Shinozaki:Three-dimensional human body shape modeling for clothing CAD, 22nd imageengineering conference, pp.235-238, 1991) However, this art only dealswith characteristics of the human body as a linear distribution andthere is no reference to a method for deriving a multidimensional shapedistribution map.

[0009] On the other hand, in a method which is already disclosed by theinventors of the present invention (Masaaki Mochimaru, Makiko Kouchi,Yukio Fukui, and Emiko Tsutsumi,Classification of 3D foot shape based oninter-shape distance using the FFD method, Japanese Journal ofErgonomics, 33(4), pp.229-234, 1997), instead of re-describing the humanbody shape using the function system, characteristics of the human bodycan be understood as the multidimensional distribution. However, themethod using the FFD by Mochimaru, et al. only solves the above problem(1) and neither problems (2) nor (3).

[0010] As the method for computing the virtual shape on the distributionmap, methods for computing the average shape and the standard deviationshape are disclosed in the article by the above Kishimoto, et al.However, since, as described above, after all, this method computes thestandard deviation shape based on the linear distribution of the humanbody shape characteristics, it cannot compute the standard deviationshape based on the multidimensional human body distribution, which is afeature of the present invention.

[0011] Furthermore, this method requires a shape to be re-describedusing the B-spline function based on the coordinate data of the shapeobtained by a shape measurement unit. In addition, in order toaccurately describe the shape using the function system, an artifice,such as one in which the number of control points of the spline functionmust be added in accordance with the sizes of concave and convex partsof the shape, must be needed. This leads to a major problem that a largeamount of preprocessing is required.

[0012] In the average shape generation method proposed by the inventorsof the present invention (Japanese Patent No. 3,106,177, method anddevice for generating average shape of a plurality of three-dimensionalshapes), there is no above mentioned preprocessing problem. However,this method is dedicated to computation of the average shape and thereis no reference to computation of the virtual shape in the periphery ofthe shape distribution map.

Problems to be Solved by the Invention

[0013] The present invention is made to solve the foregoing threeproblems, that is,

[0014] (1) creation of the distribution map of a plurality ofthree-dimensional human body shapes that are represented using numericaldata;

[0015] (2) computation of a virtual shape that is located in theperiphery of the distribution map; and

[0016] (3) provision of a consistent method and device for realizing thevirtual shape.

Means for Solving the Problems

[0017] In a method in which three-dimensional shape data of a pluralityof people is obtained by measuring the body shape thereof, amultidimensional distribution map is formed based on thethree-dimensional shape data of the plurality of people, and a virtualshape located on the periphery of the multidimensional distribution mapis formed, whereby the virtual shape is generated, the method forgenerating the virtual shapes of the plurality of three-dimensionalshapes is characterized in that a space distortion function whichmutually distorts the three-dimensional shape data of the plurality ofpeople using the free form deformation method is computed amultidimensional distribution map of the three-dimensional shape data ofthe plurality of people is generated and a virtual shape existing at anarbitrary location of the multidimensional distribution map is derived.

[0018] In a device for generating a virtual shape on a distribution mapof a plurality of three-dimensional shapes comprising athree-dimensional shape measurement unit for measuring human shapes andoutputting the measured human shapes as three-dimensional shape data ofa plurality of people, a virtual shape forming unit for forming amultidimensional distribution map based on the three-dimensional shapedata of the plurality of people and forming the virtual shape located inthe periphery of the multidimensional distribution map, and athree-dimensional realizing unit for realizing numerical data from thevirtual shape forming unit, the device for generating virtual shapes ofthe plurality of three-dimensional shapes is characterized in that thevirtual shape forming unit has functions such that a space distortionfunction which mutually distorts the three-dimensional data of theplurality of people is computed using the free form deformation method,a multidimensional distribution map of the three-dimensional shape dataof the plurality of people is generated based on the magnitude of thespace distortion, and the virtual shape of an arbitrary location of themultidimensional distribution map is derived.

BRIEF DESCRIPTION OF THE DRAWINGS

[0019]FIG. 1 is a block diagram of the overall construction of a virtualshape generation device according to the present invention.

[0020]FIGS. 2A and 2B are side and front views, respectively,illustrating anatomical landmarks of a part of a human body.

[0021]FIGS. 3A and 3B are side and front views, respectively,illustrating anatomical landmarks of an important part of the humanbody.

[0022]FIG. 4 is a distribution map illustrating an appearance of thehuman body shape distribution.

[0023]FIGS. 5A to 5C are diagrams showing modeling and foot shape databased on the anatomical landmarks;

[0024]FIGS. 6A and 6B are diagrams each showing a moving pattern of afree form deformation lattice.

[0025]FIG. 7 is a diagram showing an amount of displacement of the firstaxis of the distribution map and an amount of movement of the free formdeformation lattice.

[0026]FIGS. 8 and 8B are diagrams showing standard deviation shapes ofthe first axis of the distribution map.

[0027]FIGS. 9 and 9B are diagrams showing standard deviation shapes ofthe second axis of the distribution map.

[0028] The embodiments of the present invention are described withreference to the figures.

[0029] The device of the present invention includes a three-dimensionalshape measurement unit for inputting a human body shape, a virtual shapeforming unit for computing a multidimensional distribution map based ona plurality of human body shapes obtained by the three-dimensional shapemeasurement unit and forming a virtual shape located in the periphery ofthe multidimensional distribution map, and a three-dimensional realizingunit for realizing numerical data from the virtual shape forming unit(FIG. 1).

[0030] The outlines of the method and device according to the presentinvention are described in a sequential order of operation processing.

[0031] (1) Initially, the human body shapes of a plurality of people (Npeople) belonging to a target group are measured by the abovethree-dimensional shape measurement unit.

[0032] (2) Next, the measured human body shapes of the N people aremodeled based on anatomical characteristics of the human body and thenthese inter-shape distances are computed, whereby the multidimensionaldistribution map of the three-dimensional shapes having the distancerelationship satisfied is obtained.

[0033] (3) In order to compute the virtual shape located at an arbitrarycoordinate point of the distribution map, approximately 10 virtualshapes located on the line between the center of the distribution mapand the above arbitrary coordinate point are computed by performinginterpolation using the human body shapes of the N people.Characteristics of the virtual shapes distorting along the above lineare represented as a moving pattern of a control lattice point of thefree form deformation method whereby the amount of movement of thecontrol lattice point and the amount of movement along the line on thedistribution map are statistically related. Based on this relationship,by extrapolating the control lattice point moving pattern for distortingthe virtual shape located at the center to the virtual shape located atthe above arbitrary coordinate point and applying this control latticepoint moving pattern to the virtual shape located at the center, thevirtual shape located at the above arbitrary coordinate point iscomputed.

[0034] (4) The numerical data of the virtual shape located at the abovearbitrary coordinate point is realized using the above realizing unit.

[0035] Hereinafter, the construction of the present invention is morespecifically described.

Three-Dimensional Shape Measurement Unit

[0036] As the three-dimensional measurement unit, for example, alaser-type shape scanner (which can measure a three-dimensional body asa set of a number of three-dimensional coordinates by projecting a laserthereon) or the like is used. This three-dimensional shape measurementunit measures the human body shapes of the target group (a plurality ofpeople (number N)) The human body shape is not necessarily the wholebody and may be the shape of a specific part such as a foot or the head.The human body shape is marked with points corresponding to anatomicallandmarks whereby the location data of these characteristic points isobtained along with the three-dimensional shape data. The obtainedthree-dimensional shape data is reconstructed based on the location dataof these characteristic points. In other words, all or part of thecoordinate points measured by the three-dimensional shape measurementunit are data which are set so as to correspond to the anatomicallandmarks of the human body.

[0037] Here, in a foot shape, anatomical landmarks of the human bodyrepresent skeletal characteristic points including metatarsale fibulare,metatarsale tibiale, and pternion in FIGS. 2A and 2B. Likewise, in thetrunk part of the human body shape, anatomical landmarks of the humanbody represent skeletal characteristic points including trochanterion,acromion and thelion (bust point) in FIGS. 3A and 3B. Anatomicallandmark can be defined on the soft tissue such as the point at thejunction of the leg and foot in FIG. 5A or thelion (bust point) in FIGS.3A and 3B.

Virtual Shape Forming Unit

[0038] The virtual shape forming unit includes an input/output unit, aCPU (Central Processing Unit) for processing data, and a memory.Operations processed by this unit are sequentially described.

(1) Obtain Multidimensional Distribution Map

[0039] Initially, the virtual shape forming unit generates themultidimensional distribution map. As described above, thethree-dimensional shape measurement unit reconstructs the shape data ofthe N people based on the anatomical landmarks. The virtual shapeforming unit computes the inter-shape distance (non-similarity) of theshape data of the N people. There are two preferable methods for thiscomputation.

[0040] The first one is a method for computing the moving pattern of thecontrol lattice point based on a free form deformation method whichmutually transforms the shape data of the N people and for defining theinter-shape distance as the amount of distortion thereof. Since thedetails of this method are already disclosed in Japanese Patent No.3,106,177, they are described in detail. In short, in two shape data Aand B reconstructed using the anatomical landmarks, the control latticepoint for the free form deformation method is set around the shape dataA. When the control lattice point is appropriately moved to be distortedso that the shape data A corresponds to the shape data B, theinter-shape distance (non-similarity) between the shape data A and theshape data B is defined using the total amount of movement of thecontrol lattice point.

[0041] The second method is a method which defines as the inter-shapedistance the total of the distances between the corresponding points ofthe above-described reconstructed shape data of the N people. In theformer method, even though there is uniformity in the reconstruction ofthe shape based on the anatomical landmarks, the inter-shape distancewhich uniformly evaluates the entirety of the shape can be computed.However, computation processing takes time. By computing all of theinter-shape distances (non-similarities) among the shape data of the Npeople using any of the methods, an N×N distance matrix can be obtained.

[0042] By processing this distance matrix in the virtual shape formingunit, a shape distribution map shown in FIG. 4 can be obtained. Thisprocessing is performed using a multidimensional scaling method, whichis one of multivariate analysis methods. Although FIG. 4 shows humanbody shape distribution states of the N people in two distribution axes,coordinate computation can be performed in a distribution map havingmore dimensions (the fourth dimensions, the fifth dimensions, etc.)

(2) Computation of Center Virtual Shape

[0043] In the virtual shape forming unit, when the above distributionmap is obtained, the virtual shape located at the center (in a point inwhich the coordinates of every distribution axis are zero) of thedistribution map is obtained. In a practical sense, this virtual shapeis equivalent to what is obtained by averaging data points correspondingto shape data points of the N people, which is referred to as a centervirtual shape.

(3) Computation of Peripheral Virtual Shape (1)

[0044] A virtual shape which is located at an arbitrary coordinate pointP_(t): (p_(t1), p_(t2), p_(t3), . . . p_(ts)) of the sth dimensionalchart (s is an integer, which is 2 or greater) is computed. To do this,initially, virtual shapes on the line connected between the abovearbitrary coordinate point and the central point P_(o): (0, 0, 0 . . .0) of the distribution map are computed using interpolation.

[0045] M distribution map coordinate points on the above lines areP_(m): (p_(m1), p_(m2), p_(m3), . . . p_(ms)); m=1. . . M and coordinatepoints on the shape distribution map of the N people are P_(n): (p_(n1),p_(n2), p_(n3), . . . p_(ns)); n=1. . . N. Using a quasi-Newton'smethod, optimization computation is performed on a weighting coefficientC_(mn) (C_(mn)≧0) for computing the mth virtual shape P_(m) so that anevaluation function E defined by the following expression 1 isminimized. $\begin{matrix}{E = {\sum\limits_{i = 1}^{s}\left( {p_{m\quad i} - {\sum\limits_{n = 1}^{N}{C_{m\quad n} \cdot p_{ni}}}} \right)}} & {{Expression}\quad 1}\end{matrix}$

[0046] Coordinate points in the real space which constitute virtualshapes located at the distribution coordinate points P_(m) are V_(mk):(X_(mk), Y_(mk), Z_(mk)) ; M=1. . . M, k=1. . . K (K is the number ofvertices of the shape data reconstructed based on the anatomicallandmarks). Coordinate points in the real space which constitutethree-dimensional shapes of the N people are V_(nk): (X_(nk), Y_(nk),Z_(nk)) ; n=1. . . N, k=1. . . K. The V_(mk) is computed based on theabove weighting coefficient C_(mn) and the coordinate points V_(nk) ofthe three-dimensional shapes of the N people using the followingexpression 2. $\begin{matrix}{V_{mk} = \frac{\sum\limits_{n = 1}^{N}{C_{mn}V_{nk}}}{\sum\limits_{n = 1}^{N}C_{m\quad n}}} & {{Expression}\quad 2}\end{matrix}$

[0047] However, in this method, all of the virtual shapes located at thearbitrary points P_(m) in the distribution map cannot be computed. Sincethis method is performed by interpolation computing the virtual shapesbased on the measured shape data of the N people, the virtual shapes inperipheral regions of the distribution map cannot be computed (the aboveweighting coefficient C_(mn) cannot be identified using the optimizationcomputation). In this case, the virtual shapes are computed using thebelow-described method.

(4) Computation of Peripheral Virtual Shape (2)

[0048] The m virtual shapes on the line of the distribution map obtainedusing the above method show characteristics in which a human body shapevaries in a three dimensional manner along a specific line of thedistribution map. The tendency, in which the shape varies along the lineof the distribution map, is re-described as the control lattice pointmoving pattern of the free form deformation method. By extrapolating thecontrol lattice point moving pattern along the line of the distributionmap and applying the moving pattern to the above center virtual shape,the virtual shapes located at the arbitrary coordinate points P_(t):(p_(t1), p_(t2), p_(t3). . . p_(ts)) on the distribution map arecomputed.

[0049] Specifically, the control lattice point moving pattern of thefree form deformation method for causing the virtual shape forming unitto distort the above center virtual shape into the virtual shape locatedat the above computed distribution map coordinate point P_(m) iscomputed. Details are disclosed by the inventors of the presentinvention in Japanese Patent No. 3,106,177. in short, in two shape dataA and B reconstructed based on the anatomical landmarks, when thecontrol lattice point for the free form deformation method is set aroundthe shape data A and are appropriately moved so that the shape data Acorresponds to the shape data B, the amount of movement of the controllattice point is optimized so that the amount of movement of the controllattice point is minimized and the total of distances among points ofthe shape data A and the corresponding points of the shape data B areminimized.

[0050] In the case of the human body shape distribution, the amount ofmovement of the computed control lattice point in the real space in thedirections of the X axis, the Y axis, and the Z axis and the amount ofdisplacement between the distribution map coordinate point P_(m) and thedistribution map central point P_(o) have substantially linearrelationship. Therefore, the above amount of movement can be representedusing a regression expression based on the above amount of displacement.According to this regression expression, the amount of movement of thecontrol lattice point can be extrapolated in the distribution mapcoordinate points P_(t): (p_(t1), p_(t2), p_(t3). . . p_(ts)) that aremore periphery to the distribution map coordinate points P_(m) which canbe computed using the above method. By applying this control latticepoint moving pattern to the above center virtual shape, the peripheralvirtual shape located at the distribution map coordinate points P_(t);(p_(t1), p_(t2), p_(t3). . . p_(ts)) can be computed.

(5) Realization

[0051] The peripheral virtual shape computed using the above method isshape data constructed using a plurality of vertices (K points) based onthe anatomical landmarks. Generally speaking, K is approximately severalhundred, which is sufficient number for studying the distributioncharacteristics of the human body shape. However, it is ofteninsufficient number for being used as product compatibility evaluation.Therefore, by replacing the above-described center virtual shape withdetailed shape data having several million vertices and by applying theabove-described control lattice point movement pattern to this detailedcenter virtual shape, the detailed peripheral virtual shape havinghundreds of thousand of vertices can be compute.

[0052] This detailed peripheral virtual shape is converted intocross-sectional data. The above-described realizing unit can realize thecross-sectional data using a rapid prototyping art such as a lightmodeling method. Although, here, the light modeling method is used as anexample, other methods, such as a cutting method by a numericallycontrolled machine, may be used.

Embodiment

[0053] As an embodiment of the present invention, an example is shown inwhich the shape distribution map of 63 adult female foot shape examplesis obtained and peripheral virtual shapes on the distribution axis ofthe distribution map are computed. These shape data are obtained bymaking a plaster cast of a foot in a standing position, modeling itbased on the locations of anatomical landmarks (FIG. 5A and FIG. 5B) andinputting a data point one by one using a mechanical-arm typethree-dimensional shape measurement unit.

[0054] Although not shown in the figures, one shape data is polyhedrondata (FIG. 5C) which consists of 324 triangles, each of which isobtained by connecting data faces each having 174 points. Regarding the63 foot shape models interrelated based on the anatomical landmarks, theinter-shape distance is computed using the method according to thepresent invention. The obtained distance matrix is processed using themultidimensional scaling method.

[0055]FIG. 4 shows distribution of the first axis and the second axisamong what is obtained by computing fourth dimensional solutions usingthe multidimensional scaling method. The peripheral virtual shapes insuch locations so as to be each displaced by 3× the standard deviationsthereof from the origin of the distribution map along these two axes arecomputed.

[0056] Initially, in the proximity of the origin of the distributionmap, virtual shapes located on the distribution axis are computed usingthe expression (1) of the periphery virtual shape according to thepresent invention. In the case of this embodiment, with respect to thefirst axis, the periphery virtual shape can be computed in a range of−1.25 to +1.15 using the standard deviation as a unit, and with respectto the second axis, the periphery virtual shape can be computed in arange of −0.7 to +0.7 using the standard deviation as a unit. Hence,with respect to the first axis, virtual shapes located at −1.25, ±1.0,±0.75, ±0.5, ±0.25, and ±1.15 are computed and, with respect to thesecond axis, virtual shapes located at ±0.7, ±0.6, ±0.45, ±0.3, and±0.15 are computed. FIGS. 6A and 6B show examples of resultant virtualshapes and the moving pattern of the free form deformation methoddistorted lattice for converting the virtual shape located at the centerto the virtual shape located on these axes. FIG. 6A shows conversionfrom the shape (0, 0, 0, 0) located at the center into the virtual shapelocated at −1.0 standard deviation (−1, 0, 0, 0) on the first axis ofthe distribution map. FIG. 6B shows conversion from the shape (0, 0, 0,0) located at the center to the virtual shape located at +1.0 standarddeviation (+1, 0, 0, 0) on the first axis of the distribution map.

[0057] The amount of movement of each free form deformation methoddistorted lattice and the displacement from the central location of thedistribution map have substantially linear relationship, as shown inFIG. 7. Therefore, the amount of movement of the free form deformationmethod distorted lattice is modeled using the regression expression withrespect to displacement from the central location of the distributionmap. By complying with this regression expression, the virtual shape atmore periphery part which cannot be computed using expression (1) of theperiphery virtual shape can be computed, which is expression (2) of theperiphery virtual shape. The periphery virtual shapes at the locationsof ±3 standard deviations of the first axis computed using thisexpression are shown in FIGS. 8A (+3.0) and 8B (−3.0) The peripheryvirtual shapes at the locations of ±3 standard deviations of the secondaxis are shown in FIGS. 9A (+3.0) and 9B (−3.0).

[0058] When the shapes obtained in this manner are compared, concreteshape characteristics of each axis of the three-dimensional shapedistribution map shown in FIG. 4 can be visually recognized. Inaddition, when detailed peripheral virtual shapes are realized using thedevice according to the present invention, it is possible to evaluatethe compatibility of a product as a group by applying the peripheralvirtual shape to the product designed for the shape (“mode” shape)located at the center of this distribution map.

[0059] When a product adjusted to a customer is designed and the productis designed as not a custom-made product but a mass production productfor a group (a specific customer bracket), not only product design forthe average shape representing the group, but also compatibilityevaluation of the product to a virtual shape located in the periphery ofthe variations of the group must be needed.

[0060] When the realized periphery virtual shape obtained by the presentinvention is used, by applying a developed product to the realizedperiphery virtual shape, an allowable margin of the product isestimated. Alternatively, the product can be readjusted- An advantage ofperforming evaluation using the realized periphery virtual shape notusing a specific individual (actual person) is to solve a difficulty infinding a person located in the periphery of the group as well as to becapable of performing evaluation using a shape having only features ofthe periphery of the group excluding peculiarities of specificindividuals.

[0061] Furthermore, as shown in the present invention, by formulatingvariation characteristics on the distribution axis of the group as amoving pattern of the lattice point, shape data located at ±3 standarddeviation can be estimated from a small amount of shape data (onehundred or less people) not from an enormous amount of three-dimensionaldata (tens of thousands of people) This means that the groupcharacteristics can be estimated using the distribution model withoutcollecting a large amount of human body data. This is similar to a casein which the group characteristics can be estimated from a small amountof data when the normal distribution is assumed. That is, whengovernments, companies, or the like collect data, without performinglarge-scale measurement regarding tens of thousands of people,derivation and formation of shape distributions and periphery virtualshapes can be realized using data regarding a hundred or less people.

[0062] As described above, the present invention is described based onthe embodiment. However, the present invention is not limited to thisembodiment. It is obvious that various modifications may be made in thepresent invention without departing from the scope defined in theappended claims.

1. A method in which three-dimensional shape data of a plurality ofpeople is obtained by measuring the body shape thereof, amultidimensional distribution map is formed based on saidthree-dimensional shape data of said plurality of people, and a virtualshape located on the periphery of the multidimensional distribution mapis formed, whereby the virtual shape is generated, the method forgenerating the virtual shapes of the plurality of three-dimensionalshapes being characterized in that: a space distortion function whichmutually distorts said three-dimensional shape data of said plurality ofpeople using the free form deformation method is computed; amultidimensional distribution map of said three-dimensional shape dataof said plurality of people is generated; and a virtual shape existingat an arbitrary location of said multidimensional distribution map isderived.
 2. A device for generating a virtual shape on a distributionmap of a plurality of three-dimensional shapes comprising: athree-dimensional shape measurement unit for measuring human shapes andoutputting the measured human shapes as three-dimensional shape data ofa plurality of people; a virtual shape forming unit for forming amultidimensional distribution map based on said three-dimensional shapedata of said plurality of people and forming the virtual shape locatedin the periphery of said multidimensional distribution map; and athree-dimensional realizing unit for realizing numerical data from saidvirtual shape forming unit, the device for generating virtual shapes ofthe plurality of three-dimensional shapes characterized in that saidvirtual shape forming unit has functions such that: a space distortionfunction which mutually distorts said three-dimensional data of saidplurality of people is computed using the free form deformation method;a multidimensional distribution map of said three-dimensional shape dataof said plurality of people is generated based on the magnitude of thespace distortion; and the virtual shape of an arbitrary location of saidmultidimensional distribution map is derived.